Resource allocation apparatus, resource allocation method, and computer readable medium

ABSTRACT

A parameter determination unit  110  substitutes, for each of a plurality of applications, a recommended amount of resources and a quality of experience corresponding to the recommended amount of resources, and a minimum amount of resources and a quality of experience corresponding to the minimum amount of resources into a quality function fin expression (1) indicating a relation between an amount of resources R and a quality of experience Q, to determine parameters a and b. A resource amount determination unit  120  determines an amount of resources to be allocated to the plurality of applications using the quality function f for each application in which the parameters a and b are determined. The quality function f(x) is a monotonically increasing function having an inverse function f −1 , connects (−∞) and (+∞), and is symmetrical with respect to x= 0.    
         Q=f ( x )= f (( R−a )/ b )   (1).

TECHNICAL FIELD

The present invention relates to a technique for allocating resources to a plurality of applications operated on a computer.

BACKGROUND ART

Various techniques have been suggested to allocate resources in a computer system.

For example, a QoS control apparatus disclosed in PTL 1 registers, in a table, an amount of resources to be assigned corresponding to the class of QoS that is determined in advance for a task that is being operated in an assignment amount registration means, and determines the resource allocation amount to each task based on the table.

Further, a distributed resource management system disclosed in PTL 2 creates, when resources to be shared by a plurality of applications are allocated, a demand function indicating the degree of demand of target resources required for the plurality of applications, to allocate the resources based on the demand function.

Small-sized devices such as mobile telephones, PNDs (Portable Navigation Devices), and DPFs (Digital Photo Frames) have limited resources of memory capacities and arithmetic capacities of CPUs. Thus, allocation of resources to applications is especially important. When a large number of applications are operated in these small-sized devices, these applications may not be able to operate as expected. This is because, since these applications contend for the limited resources, it is impossible to achieve the quality which can be accomplished in the case in which only one application is operated.

In order to smoothly operate a plurality of applications in a device with limited resources, it is required to appropriately allocate the resources to these applications. Since the appropriate allocation of resources is different depending on the number and the type of the applications that are operated, methods like equal allocation and best effort allocation are not preferable.

One known method is to calculate, for each of the plurality of applications that are being operated, the amount of resources to be allocated to each of the applications based on a relation between an amount of resources to be used by the application and a quality of user experience. The quality of user experience means the degree of satisfaction felt by users. The user satisfaction can be enhanced by performing resource allocation based on the quality of user experience.

CITATION LIST Patent Literature

-   PTL 1: Japanese Unexamined Patent Application Publication No.     2000-155695 -   PTL 2: Japanese Unexamined Patent Application Publication No.     11-66018

SUMMARY OF INVENTION Technical Problem

For example, one possible method is, with the application of the technique disclosed in PTL 1, for each application, a table indicating a relation between an amount of resources to be used by the application and the quality of experience is registered in advance, and allocation of resources is performed to these applications based on the table of each application that is operated.

Further, the table indicating the relation between the amount of resources to be used by the applications and the quality of experience may be created in advance by manufacturers of the applications and designers of the devices, for example.

However, recent mobile telephones include, however, even though they are small-sized devices, several tens of applications installed therein. In such a case, it requires a huge amount of energy to preliminary search the relation between the amount of resources to be used and the quality of experience for each application for the device on which a large number of applications are installed.

The present invention has been made based on the background stated above, and provides a technique to efficiently acquire the relation between the amount of resources to be used by each application and the quality of experience when the amount of resources is allocated to a plurality of applications operated on a device.

Solution to Problem

One exemplary aspect of the present invention is a resource allocation apparatus that performs allocation of an amount of resources to a plurality of applications operated on a computer. This resource allocation apparatus includes a parameter determination unit and a resource amount determination unit.

The parameter determination unit determines, for each of the plurality of applications, a first parameter a and a second parameter b in a quality function f of expression (1) indicating a relation between an amount of resources to be used and a quality of user experience. More specifically, for each of the applications, a recommended amount of resources and a quality of experience corresponding to the recommended amount of resources, and a minimum amount of resources and a quality of experience corresponding to the minimum amount of resources are substituted into expression (1), to calculate the first parameter a and the second parameter b in expression (1). Note that the quality function f(x) is a monotonically increasing function having an inverse function f⁻⁻¹, connects (−∞, 0) and (+∞, 1), and is symmetrical with respect to x=0.

Q=f(x)=f((R−a)/b)   (1)

where

Q: quality of experience

f: quality function

R: amount of resources

a: first parameter

b: second parameter

The resource amount determination unit determines an amount of resources to be allocated to the plurality of applications using the quality function f for each of the plurality of applications in which the first parameter a and the second parameter b are determined by the parameter determination unit.

Note that a method and a system with which the resource allocation apparatus according to the above aspect is replaced, a program for causing a computer to execute the operation of the resource allocation apparatus, a computer readable recording medium storing the program, and the like are also effective as aspects of the present invention.

Advantageous Effects of Invention

According to the technique of the present invention, it is possible to efficiently create a quality function which indicates a relation between an amount of resources to be used and a quality of user experience and is required to allocate resources to a plurality of applications.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram showing a resource allocation apparatus according to a first exemplary embodiment of the present invention;

FIG. 2 is a diagram showing a quality function f;

FIG. 3 is a diagram showing two specific examples of the quality function f;

FIG. 4 is a flowchart showing a process flow in the resource allocation apparatus shown in FIG. 1;

FIG. 5 is a diagram showing an example of a relation between performance of applications and an amount of resources;

FIG. 6 is a diagram showing a quality function created for three applications shown in FIG. 5;

FIG. 7 is a diagram for describing determination of an amount of resources for the three applications shown in FIG. 5;

FIG. 8 is a diagram showing a resource allocation apparatus according to a second exemplary embodiment of the present invention;

FIG. 9 is a diagram showing an example of a reception unit in the resource allocation apparatus shown in FIG. 8 (case 1);

FIG. 10 is a diagram showing an example of the reception unit in the resource allocation apparatus shown in FIG. 8 (case 2);

FIG. 11 is a flowchart showing a process flow in the resource allocation apparatus shown in FIG. 8;

FIG. 12 is a diagram for describing an example of allocation of an amount of resources by the resource allocation apparatus shown in FIG. 8;

FIG. 13 is a diagram showing a resource allocation apparatus according to a third exemplary embodiment of the present invention;

FIG. 14 is a diagram for describing an example of allocation of an amount of resources by the resource allocation apparatus shown in FIG. 13; and

FIG. 15 is a flowchart showing a process flow in the resource allocation apparatus shown in FIG. 13.

DESCRIPTION OF EMBODIMENTS

Hereinafter, with reference to the drawings, exemplary embodiments of the present invention will be described. For the clarification of description, the following description and the drawings are omitted and simplified as appropriate. Further, each element shown in the drawings as functional blocks performing various processing may be formed of a CPU, a memory, and other circuits in hardware, and may be achieved by a program loaded to a memory in software. Accordingly, a person skilled in the art would understand that these functional blocks may be achieved in various ways, e.g., only by hardware, only by software, or the combination thereof without any limitation. Throughout the drawings, the identical components are denoted by the identical reference symbols, and overlapping description is omitted as appropriate.

Further, the program mentioned above can be stored and provided to a computer using any type of non-transitory computer readable media. Non-transitory computer readable media include any type of tangible storage media. Examples of non-transitory computer readable media include magnetic storage media (such as flexible disks, magnetic tapes, hard disk drives, etc.), optical magnetic storage media (e.g. magneto-optical disks), CD-ROM (Read Only Memory), CD-R, CD-R/W, and semiconductor memories (such as mask ROM, PROM (programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory), etc.). The program may be provided to a computer using any type of transitory computer readable media. Examples of transitory computer readable media include electric signals, optical signals, and electromagnetic waves. Transitory computer readable media can provide the program to a computer via a wired communication line (e.g. electric wires, and optical fibers) or a wireless communication line.

First Exemplary Embodiment

FIG. 1 shows a resource allocation apparatus 100 according to a first exemplary embodiment of the present invention. This resource allocation apparatus 100 is installed in a small-sized device such as a mobile telephone, and performs allocation of resources to applications operated on the small-sized device.

The resource allocation apparatus 100 includes a parameter determination unit 110 and a resource amount determination unit 120.

The parameter determination unit 110 determines, for each of a plurality of applications activated by the small-sized device, a first parameter a_(i) and a second parameter b_(i) in a quality function f of expression (2) indicating a relation between an amount of resources to be used and a quality of user experience.

Q _(i) =f(x)=f((R _(i) −a _(i))/b _(i))   (2)

where

i: number of application

Q_(i): quality of experience

f: quality function

R_(i): amount of resources

a_(i): first parameter

b_(i): second parameter

As shown in FIG. 2, the quality function f(x) is a monotonically increasing function having an inverse function f⁻⁻¹, connects (−∞, 0) and (+∞, 1), and is symmetrical with respect to x=0.

As the quality function f(x) which is a monotonically increasing function, such a function is employed in which values are gradually increased from (−∞, 0), the slope increases as x approaches 0, gradually decreases after x=0, and coordinates gradually approach (+∞, 1). The reason why the monotonically increasing function f(x) having such characteristics is used as the quality function is that it is possible to reproduce the characteristics of the quality of user experience that is assumed. This assumption is as follows. That is, if the performance is sufficiently accomplished, the user does not feel that the quality has improved even when the performance is somewhat further enhanced, whereas if the performance is hardly accomplished, the user does not feel that the quality has reduced even when the performance is further decreased. While the quality function f(x) is preferably continuous and smooth, it may be approximately continuous and smooth.

FIG. 3 shows two specific examples of the quality function f(x). The solid line and the dotted line indicate f(x) in expression (3) and expression (4), respectively. The symbol “x” in expression (3) and expression (4) is “(R−a)/b”.

$\begin{matrix} {{f(x)} = \frac{1}{1 + ^{- x}}} & (3) \\ {{f(x)} = {{\frac{1}{\pi}{\arctan (x)}} + \frac{1}{2}}} & (4) \end{matrix}$

While the one shown in expression (3) is used as an example of f(x) in the following description, the quality function is not limited to the function shown in expression (3).

Substituting, for each application, a recommended amount of resources R_(i) ^(high) and a quality of experience Q_(i) ^(high) corresponding to the recommended amount of resources R_(i) ^(high), and a minimum amount of resources R_(i) ^(low) and a quality of experience Q_(i) ^(low) corresponding to the minimum amount of resources R_(i) ^(low) of the application into expression (3) gives the following expression (5) and expression (6). Note that R_(i) ^(high), Q_(i) ^(high), R_(i) ^(low) and Q_(i) ^(low) are determined by manufacturers of the applications or designers of the devices, and are input to the parameter determination unit 110.

$\begin{matrix} \left\{ \begin{matrix} {Q_{i}^{high} = \frac{1}{1 + ^{- \frac{R_{i}^{high} - a_{i}}{b_{i}}}}} \\ {Q_{i}^{low} = {\frac{1}{1 + ^{- \frac{R_{i}^{low} - a_{i}}{b_{i}}}}(6)}} \end{matrix} \right. & (5) \end{matrix}$

Then, solving the simultaneous equations of expression (5) and expression (6) for a_(i) and b_(i) obtains the first parameter a_(i) and the second parameter b_(i) as shown in expressions (7) and (8).

$\begin{matrix} \left\{ \begin{matrix} {a_{i} = \frac{{R_{i}^{low}{\ln\left( {\frac{1}{Q_{i}^{high}} - 1} \right)}} - {R_{i}^{high}{\ln\left( {\frac{1}{Q_{i}^{low}} - 1} \right)}}}{{\ln \left( {\frac{1}{Q_{i}^{high}} - 1} \right)} - {\ln\left( {\frac{1}{Q_{i}^{low}} - 1} \right)}}} \\ {b_{i} = {\frac{R_{i}^{low} - R_{i}^{high}}{{\ln \left( {\frac{1}{Q_{i}^{high}} - 1} \right)} - {\ln\left( {\frac{1}{Q_{i}^{low}} - 1} \right)}}(8)}} \end{matrix} \right. & (7) \end{matrix}$

The parameter determination unit 110 calculates the first parameter a_(i) and the second parameter b_(i) for each application according to expressions (7) and (8) to supply the calculated results to the resource amount determination unit 120.

When Q_(i) ^(high) and Q_(i) ^(low) satisfy the following expression (9), the calculation of the first parameter a_(i) and the second parameter b_(i) becomes simple as shown in expression (10) and FIG. 11).

Q _(i) ^(high) +Q _(i) ^(low)=1   (9)

$\begin{matrix} \left\{ \begin{matrix} {a_{i} = \frac{R_{i}^{low} + R_{i}^{high}}{2}} \\ {b_{i} = {\frac{R_{i}^{low} - R_{i}^{high}}{2{\ln \left( {\frac{1}{Q_{i}^{high}} - 1} \right)}}(11)}} \end{matrix} \right. & (10) \end{matrix}$

When Q_(i) ^(high) and Q_(i) ^(low) satisfy expression (9), the first parameter a_(i) shown in expression (9) is an average value of the recommended amount of resources R_(i) ^(high) and the minimum amount of resources R_(i) ^(low). This is satisfied not only in the quality function f(x) shown in expression (3) but also in any monotonically increasing function that has an inverse function f⁻⁻¹, connects (−∞, 0) and (+∞, 1), and is symmetrical with respect to x=0. This average value indicates an amount of resources when the quality Q is 0.5.

The resource amount determination unit 120 determines, using the first parameter a and the second parameter b of each application determined by the parameter determination unit 110, the amount of resources to be allocated to these applications.

In the first exemplary embodiment, the resource amount determination unit 120 determines the amount of resources to be allocated to each application so that the total amount of resources to be allocated to each application is a predetermined amount TR and the quality of experience of each application becomes the same. This quality of experience is hereinafter called a uniform quality of experience AQ.

More specifically, the resource amount determination unit 120 determines the amount of resources Ri for each application according to expressions (12) and (13).

$\begin{matrix} {{AQ} = {f\left( \frac{{TR} - {\sum\limits_{i}a_{i}}}{\sum\limits_{i}b_{i}} \right)}} & (12) \end{matrix}$

where

-   AQ: uniform quality of experience -   TR: predetermined amount

R _(i) =b _(i) f ⁻⁻¹(AQ)+a _(i)   (13)

where

-   AQ: uniform quality of experience

Note that the predetermined amount TR is set by a designer of the device, for example. Specifically, for example, it is possible to determine the amount of resources that can be used to execute the applications among the amount of resources of the small-sized device.

FIG. 4 is a flowchart showing a process flow in the resource allocation apparatus 100 shown in FIG. 1.

First, the parameter determination unit 110 substitutes, for each application, the recommended amount of resources R_(i) ^(high) and the quality of experience Q^(i) ^(high) corresponding thereto, and the minimum amount of resources R_(i) ^(low) and the quality of experience Q_(i) ^(low) corresponding thereto into the simultaneous equations shown by expression (5) and expression (6) stated above to calculate the first parameter a_(i) and the second parameter b_(i) (S100).

The resource amount determination unit 120 substitutes the first parameter a_(i) and the second parameter b_(i) of each application calculated by the parameter determination unit 110 into expression (12), to calculate the uniform quality of experience AQ (S102).

Then, the resource amount determination unit 120 substitutes, for each application, the first parameter a_(i) and the second parameter b_(i) of the application and the uniform quality of experience AQ calculated in Step S102 into expression (13), to calculate the amount of resources Ri to be allocated to the application (S104).

Now, the resource allocation apparatus 100 shown in FIG. 1 will be described more detail using the following specific examples.

For example, the resources which are to be allocated is CPU arithmetic capacity of the device, and the amount of resources (predetermined amount TR stated above) that can be allocated to applications is 100%. There are three types of applications that are activated: a decoder compliant with H.264 (hereinafter referred to as an H.264 decoder), an application for facial recognition (hereinafter referred to as a facial recognition AP), and an application for news viewing (hereinafter referred to as a news viewing AP).

The H.264 decoder is an application for decoding a file of H.264 format which is a video codec, and the facial recognition AP is an application for analyzing an input image from a camera included in the device to judge whether the face is displayed. The news viewing AP is an application for acquiring and displaying news at predetermined intervals.

Further, it is assumed that the relation between the amount of resources to be used and the performance is obtained as shown in FIG. 5 for the three applications. In the example shown in FIG. 5, the performance of the H.264 decoder is indicated by time required to decode 30 frames, the performance of the facial recognition AP is indicated by time required to analyze one frame, and the performance of the news viewing AP is indicated by intervals to acquire the news.

Further, for each application, it is assumed that the quality of experience Q_(i) ^(high) corresponding to the recommended amount of resources R_(i) ^(high) is 0.8 and the quality of experience Q_(i) ^(low) corresponding to the minimum amount of resources R_(i) ^(low) is 0.2.

The parameter determination unit 110 determines the recommended amount of resources R_(i) ^(high) and the minimum amount of resources R_(i) ^(low) based on the relation between the performance and the application shown in FIG. 5. The determination of the recommended amount of resources R_(i) ^(high) and the minimum amount of resources R_(i) ^(low) is performed based on the standards in which it is sufficient to decode 30 frames in one second for the H.264 decoder, it is desired to analyze one frame in 0.5 to 1 second for the facial recognition AP, it is desired to acquire the news at intervals of one second for the news viewing AP, and the like.

In this way, for example, for the H.264 decoder, R_(i) ^(high) and R_(i) ^(low) are 70% and 60%, respectively, for the facial recognition AP, R_(i) ^(high) and R_(i) ^(low) are 80% and 40%, respectively, and for the news viewing AP, R_(i) ^(high) and R_(i) ^(low) are 30% and 10%, respectively.

The parameter determination unit 110 substitutes, for each application, Q^(i) ^(high) (in this example, 0.8), R_(i) ^(high), Q_(i) ^(low) (in this example, 0.2), and R_(i) ^(low) into expressions (5) and (6) to solve the first parameter a_(i) and the second parameter b_(i). In this example, for the H.264 decoder, the first parameter a_(i) and the second parameter b_(i) are 65 and 3.6, respectively. For the facial recognition AP, the first parameter a_(i) and the second parameter b_(i) are 60 and 14.4, respectively, and the first parameter a_(i) and the second parameter b_(i) are 20 and 7.2, respectively.

Accordingly, the quality functions of the H.264 decoder, the facial recognition AP, and the news viewing AP are as shown in FIG. 6.

Then, the resource amount determination unit 120 determines the amount of resources to be allocated to each application using each quality function shown in FIG. 6. More specifically, the uniform quality of experience AQ is calculated first according to expression (12), and then the amount of resources Ri to be allocated to each application is calculated by expression (13). Note that the total amount of resources to be allocated to each application is 100%.

In this example, as shown in FIG. 7, the uniform quality of experience AQ is 0.14. Further, the amount of resources of 59%, 34%, and 7% are allocated for the H.264 decoder, the facial recognition AP, and the news viewing AP, respectively.

As described above, the resource allocation apparatus 100 according to this exemplary embodiment uses the monotonically increasing function f(x) described above as the quality function when the amount of resources is allocated to the applications. Thus, only the data that is required to be prepared in advance for one application to determine the parameters of the quality function is the recommended amount of resources R_(i) ^(high) and the quality of experience Q_(i) ^(high) corresponding thereto, and the minimum amount of resources R_(i) ^(low) and the quality of experience Q_(i) ^(low) corresponding thereto. Accordingly, the efficiency to create the quality function is improved, and the burden on developers of the applications and designers of the devices can be greatly reduced. While R_(i) ^(high) and R_(i) ^(low) are determined based on the relation between the amount of resources and the performance of the application as shown in FIG. 5 in the description above, R_(i) ^(high) and R_(i) ^(low) itself may be directly supplied to the parameter determination unit 110.

Further, the quality function f(x) has characteristics in which the quality of experience is raised at around the minimum amount of resources, and stops rising at around the recommended amount of resources, thereby being able to achieve resource allocation according to user's intuition.

Further, the determination of the allocation of the amount of resources using the quality function in which the first parameter a and the second parameter b are determined can be analytically performed without searching all the combinations, thereby being able to cut the calculation cost. Therefore, even when the allocation calculation is performed in real time, the calculation overhead required to allocate the amount of resources can be reduced.

Second Exemplary Embodiment

FIG. 8 shows a resource allocation apparatus 200 according to a second exemplary embodiment of the present invention. The resource allocation apparatus 200 is also installed in a small-sized device such as a mobile telephone, for example, and allocates resources to applications operated on the small-sized device.

The resource allocation apparatus 200 includes a parameter determination unit 210, a reception unit 220, a parameter adjustment unit 230, and a resource amount determination unit 240.

The parameter determination unit 210 performs the similar processing as the parameter determination unit 110 in the resource allocation apparatus 100 shown in FIG. 1. That is, the parameter determination unit 210 calculates, for each of the plurality of applications activated in the small-sized device, the first parameter a_(i) and the second parameter b_(i) in the quality function f of expression (2) indicating the relation between the amount of resources to be used and the quality of user experience.

The first parameter a_(i) and the second parameter b_(i) of each application calculated by the parameter determination unit 210 are output to the parameter adjustment unit 230 from the parameter determination unit 210.

The reception unit 220 is a user interface that is able to receive an increase/decrease request for each application. This user interface is to input, for each of the applications, the increase/decrease request indicating whether the user desires to increase or decrease the amount of resources and the increase/decrease amount.

The parameter adjustment unit 230 adjusts the first parameter a_(i) and the second parameter b_(i) output from the parameter determination unit 210, and outputs the first parameter a_(i) and the second parameter b_(i) after adjustment to the resource amount determination unit 240. In order to differentiate the first parameter a_(i) and the second parameter b_(i) obtained by the parameter determination unit 210, the first parameter a_(i) and the second parameter b_(i) adjusted by the parameter adjustment unit 230 are denoted by the symbols a_(i)′ and b_(i)′.

The parameter adjustment unit 230 determines an adjustment factor c_(i) according to the increase/decrease request input by the user through the reception unit 220, and performs adjustment as shown in expressions (14) and (15) using the adjustment factor c_(i) that is determined.

a _(i) ′=c _(i) ×a _(i)   (14)

b _(i) ′=c _(i) ×b _(i)   (15)

The default value of the adjustment factor c_(i) is 1 for all the applications. When the increase/decrease request is not input by the user, the parameter adjustment unit 230 uses the default value of the adjustment factor c_(i).

In summary, when the increase/decrease request is not input by the user, a_(i)′ and a_(i) are equal to each other, and b_(i)′ and b_(i) are equal to each other.

When the increase/decrease request is the increase request of the amount of resources, the parameter adjustment unit 230 multiplies the adjustment factor c_(i) by the first parameter a_(i) and the second parameter b_(i). In this case, the adjustment factor c_(i) is larger than 1, and becomes larger as the amount that is desired to increase is larger. On the other hand, when the increase/decrease request is the decrease request of the amount of resources, the parameter adjustment unit 230 multiplies the adjustment factor c_(i) by the first parameter a_(i) and the second parameter b_(i). In this case, the adjustment factor c_(i) is smaller than 1, and becomes smaller as the amount that is desired to decrease is smaller.

FIG. 9 shows one example of the reception unit 220 to receive increase/decrease requests. As shown in FIG. 9, the reception unit 220 includes two adjustment buttons (adjustment button 222 and adjustment button 224) for each of the applications (AP1, AP2, AP3, . . . ).

The adjustment button 222 is pressed when it is desired to increase the amount of resources, and the number of times that the button is pressed is in direct proportion to the amount that is desired to increase. Hereinafter, the adjustment button 222 is referred to as an increase button.

The adjustment button 224 is pressed when it is desired to decrease the amount of resources, and the number of times that the button is pressed is in direct proportion to the amount that is desired to decrease. Hereinafter, the adjustment button 224 is referred to as a decrease button.

The parameter adjustment unit 230 determines, as shown in expression (16) and expression (17), for example, the adjustment factor c_(i) according to the number of times m_(i) that the increase button 222 is pressed and the number of times n_(i) that the decrease button 224 is pressed.

c _(i)=1+0.1×m _(i)   (16)

where

m_(i): the number of times that the increase button 222 is pressed

c _(i)=1−0.1×n _(i)   (17)

where

n_(i): the number of times that the decrease button 224 is pressed

FIG. 10 shows another example of the reception unit 220. As shown in FIG. 10, an adjustment bar 226 is provided for each of the applications (AP1, AP2, AP3, . . . ).

When the adjustment bar 226 is moved upward from the default position, the parameter adjustment unit 230 adds the value according to the moved distance to 1 to obtain the adjustment factor Meanwhile, when the adjustment bar 226 is moved downward from the default position, the parameter adjustment unit 230 subtracts the value according to the moved distance from 1 to obtain the adjustment factor

The parameter adjustment unit 230 outputs, for each application, the first parameter a_(i)′ and the second parameter obtained by multiplying the first parameter a_(i) and the second parameter b_(i) by the adjustment factor c_(i) to the resource amount determination unit 240. For the application that does not receive the increase/decrease requests, a_(i)′ and a_(i) are equal to each other, and b_(i)′ and b_(i) are equal to each other.

The resource amount determination unit 240 uses the first parameter after adjustment and the parameter after adjustment as the first parameter and the second parameter, and further determines the amount of resources to be allocated to each application according to (18) in the resource allocation apparatus 100. The resource amount determination unit 240 determines the amount of resources to be allocated to each application by the similar operation as 130.

In summary, according to this exemplary embodiment, the quality function is as shown in expression (18).

$\begin{matrix} \begin{matrix} {Q_{i} = {f(x)}} \\ {= {f\left( {\left( {R_{i} - a_{i}^{\prime}} \right)/b_{i}^{\prime}} \right)}} \\ {= {f\left( {{\left( {R_{i} - {c_{i} \times a_{i}}} \right)/c_{i}} \times b_{i}} \right)}} \end{matrix} & (18) \end{matrix}$

where

i: number of application

Q_(i): quality of experience

f: quality function

R_(i): amount of resources

a_(i): first parameter before adjustment

b_(i): second parameter before adjustment

a_(i)′: first parameter after adjustment

b_(i)′: second parameter after adjustment

e that expression (18) is equal to the following expression (19).

Q _(i) 32 f(x)=f((R _(i) /c _(i) −a _(i))/b _(i))   (19)

As will be clear from expression (19), the quality function obtained when the values of the first parameter a_(i) and the second parameter b_(i) are adjusted is equal to the quality function obtained by multiplying the original recommended amount of resources R_(i) ^(high) and the minimum amount of resources R_(i) ^(low) by and c_(i) indicates a parameter multiplying the recommended amount of resources R_(i) ^(high) and the minimum amount of resources R_(i) ^(low) by c_(i). In short, it can be said that the symbol c_(i) is a parameter that is set when the original amount of allocation of the amount of resources is desired to be changed according to the ratio when the application is more important or not important for the user under a certain situation.

FIG. 11 is a flowchart showing a process flow in the resource allocation apparatus 200. First, the parameter determination unit 210 substitutes, for each application, the recommended amount of resources R_(i) ^(high) and the quality of experience Q_(i) ^(high) corresponding thereto and the minimum amount of resources R_(i) ^(low) and the quality of experience Q_(i) ^(low) corresponding thereto into the simultaneous equations shown by expressions (5) and (6) stated above, to calculate the first parameter a_(i) and the second parameter b_(i) (S110). The first parameter a_(i) and the second parameter b_(i) are input to the parameter adjustment unit 230.

For the application in which it is not required to increase or decrease the amount of resources through the reception unit 220 (S112: No), the parameter adjustment unit 230 outputs the first parameter a_(i) and the second parameter b_(i) to the resource amount determination unit 240 without any adjustment.

On the other hand, for the application in which it is required to increase or decrease the amount of resources through the reception unit 220 (S112: Yes), the parameter adjustment unit 230 outputs values obtained by multiplying the first parameter a_(i) and the second parameter b_(i) of the application by the adjustment factor according to the increase/decrease request to the resource amount determination unit 240 (S114).

The resource amount determination unit 240 calculates the uniform quality of experience AQ using the first parameter and the second parameter after adjustment output from the parameter adjustment unit 230, and calculates, for each application, the amount of resources corresponding to the uniform quality of experience AQ as the amount of resources Ri to be allocated to the application (S116, S118).

For example, in the case of three applications shown in FIG. 5 (H.264 decoder, facial recognition AP, news viewing AP), it is assumed that the increase/decrease request in which c_(i) is 0.5 is input to the H.264 decoder, and the increase/decrease request is not input to the other two applications.

In this case, the quality function corresponding to the three applications is as shown in FIG. 12. Further, the uniform quality of experience AQ is 0.37, and the amount of resources allocated to the H.264 decoder, the facial recognition AP, and the news viewing AP are 32%, 52%, and 16%, respectively.

This case corresponds to the case in which the decoder is not important in a certain situation and it is sufficient that the decoder is able to perform decoding at 15 frame/sec, which is half the normal decoder. According to the resource allocation apparatus 200, the amount of resources to be allocated to the H.264 decoder in this case is decreased from 59% in the resource allocation apparatus 100 to 32%, which means it is possible to allocate the reduced resources to other applications.

In short, according to the resource allocation apparatus 200 of the second exemplary embodiment, it is possible to obtain the similar effect as in the resource allocation apparatus 100 according to the first exemplary embodiment, and to reflect the user's intention on the allocation of the amount of resources.

Third Exemplary Embodiment

FIG. 13 shows a resource allocation apparatus 300 according to a third exemplary embodiment of the present invention. This resource allocation apparatus 300 includes a parameter determination unit 310, a resource number controller 320, and a resource amount determination unit 330.

The resource allocation apparatus 300 according to the third exemplary embodiment is able to control the number of resources to be allocated to the applications when there are the same type of a plurality of resources. For example, the number of resources of “CPU arithmetic capacity” that exist in a device in which a plurality of CPU cores are installed corresponds to the number of CPU cores.

The parameter determination unit 310 performs the similar operation as the parameter determination unit 110 in the resource allocation apparatus 100, and calculates the first parameter a_(i) and the second parameter b_(i) for each application, to output the result to the resource amount determination unit 330.

The resource amount determination unit 330 calculates the uniform quality of experience AQ using the first parameter a_(i) and the second parameter b_(i) from the parameter determination unit 310, to output the result to the resource number controller 320. The method of calculating the uniform quality of experience AQ is similar to the method of calculation 130 in the resource allocation apparatus 100. However, it should be noted that the predetermined amount TR which is the total amount of resources to be allocated to the applications used in this calculation is supplied from the resource number controller 320.

The resource number controller 320 performs control so that the number of resources to be allocated to the applications becomes the minimum number under a condition that the uniform quality of experience AQ is equal to or larger than a predetermined threshold when there are the same type of a plurality of resources. For the sake of clarity, description will be made taking as an example a case in which three applications shown in FIG. 5 (H.264 decoder, facial recognition AP, news viewing AP) are installed. Further, it is assumed that the threshold of the uniform quality of experience AQ is set to 0.5.

The resource number controller 320 first supplies the arithmetic capacity (100%) of one CPU core as a predetermined amount TR to the resource amount determination unit 330.

As shown in FIG. 14, when the predetermined amount TR is 100%, the uniform quality of experience AQ calculated by the resource amount determination unit 330 is 0.14, as is similar to the case of the resource allocation apparatus 100 according to the first exemplary embodiment. In accordance therewith, the amount of resources Ri to be allocated to the H.264 decoder, the facial recognition AP, and the news viewing AP are 59%, 34%, and 7%, respectively, as is similar to the resource allocation apparatus 100 according to the first exemplary embodiment.

The resource number controller 320 compares the uniform quality of experience AQ calculated by the resource amount determination unit 330 with the threshold (in this example, 0.5). Since the current uniform quality of experience AQ is 0.14, which is smaller than the threshold, the resource number controller 320 changes the predetermined amount TR to the value (e.g., 200%) corresponding to the case in which two CPU cores are provided, to output the result to the resource amount determination unit 330, to cause the resource amount determination unit 330 to perform re-calculation of the uniform quality of experience AQ.

The resource amount determination unit 330 re-calculates the uniform quality of experience AQ using the predetermined amount TR that is changed, to output the calculation result to the resource number controller 320. The uniform quality of experience AQ at this time is, as shown in FIG. 14, 0.9.

Since the uniform quality of experience AQ exceeds the threshold 0.5, the resource number controller 320 determines the number of CPU cores to two, to cause the resource amount determination unit 330 to perform determination of allocation of the amount of resources. As shown in FIG. 14, the amount of resources Ri to be allocated to the H.264 decoder, the facial recognition AP, and the news viewing AP is 73%, 91%, and 36%, respectively, corresponding to the uniform quality of experience AQ which is 0.9.

Incidentally, the allocation according to the amount of resources Ri that is calculated above may not be achieved in reality. For example, when the applications are not parallelized and thus cannot be executed by a plurality of CPUs, it is impossible to allocate the amount of resources of 200% with the allocation rate of 73%, 91%, and 36%.

In this exemplary embodiment, the resource amount determination unit 330 includes a function of adjusting the amount of resources that is determined so that they can further be allocated. For example, for each application, the amount of resources is adjusted under the assumption that the quality of experience is equal to or larger than the threshold. In the example above, for example, the amount of resources is changed to 100% for the facial recognition AP having the largest amount of resources that is determined, and the rest of 100% is re-allocated for the H.264 decoder and the news viewing AP. Therefore, after adjustment, the amount of resources of the H.264 decoder, the facial recognition AP, and the news viewing AP is 70%, 100%, and 30%, respectively.

FIG. 15 is a flowchart showing a process flow in the resource allocation apparatus 300. First, the parameter determination unit 310 substitutes, for each application, the recommended amount of resources R_(i) ^(high) and the quality of experience Q^(i) ^(high) corresponding thereto, and the minimum amount of resources R_(i) ^(low) and the quality of experience Qi^(lowQL) corresponding thereto into the simultaneous equations shown in expression (5) and expression (6) stated above, to calculate the first parameter a_(i) and the second parameter b_(i) (S150). These first parameter a_(i) and second parameter b_(i) are output to the resource amount determination unit 330.

The resource amount determination unit 330 calculates the uniform quality of experience AQ so that the total amount of resources to be allocated to each application becomes the predetermined amount TR in the case in which one CPU core is used, to output the result to the resource number controller 320 (S152).

When the uniform quality of experience AQ output from the resource amount determination unit 330 is smaller than a predetermined threshold (S154: No), the resource number controller 320 increments the number of resources by one, to output the corresponding predetermined amount TR to the resource amount determination unit 330 (S156).

The resource amount determination unit 330 re-calculates the uniform quality of experience AQ using the predetermined amount TR that is reset by the resource number controller 320 (S152-).

The processing from Step S152 is repeated until when the uniform quality of experience AQ reaches the threshold or more (S154: No, S156, S152-).

When the uniform quality of experience AQ from the resource amount determination unit 330 is equal to or larger than the threshold (S154: Yes), the resource number controller 320 determines the current number of resources as the number of resources to be used, and the resource amount determination unit 330 determines the amount of resources of each application corresponding to the current uniform quality of experience AQ (S160).

Then, when it is possible to perform allocation according to the amount of resources that is determined (S162: Yes), the resource amount determination unit 330 performs allocation according to the amount of resources that is determined. On the other hand, when it is impossible to perform allocation according to the amount of resources that is determined (S162: No), the resource amount determination unit 330 adjusts the amount of resources that is determined so they can be allocated (S164).

According to the resource allocation apparatus 300 according to this exemplary embodiment, it is possible to obtain the effects of the resource allocation apparatus 100. Further, when there are the same type of a plurality of resources, the number of resources is minimized under a condition that the uniform quality of experience AQ is equal to or larger than the threshold, thereby being able to suppress excessive consumption of resources and to reduce power consumption.

The present invention has been described with reference to the exemplary embodiments. However, the exemplary embodiments are merely examples, and various changes, modifications, and combinations may be added to each exemplary embodiment stated above without departing from the spirit of the present invention. A person skilled in the art would understand that the variant examples in which the changes, modifications, and combinations are made are also within the scope of the present invention.

This application claims the benefit of priority, and incorporates herein by reference in its entirety, the following Japanese Patent Application No. 2010-054283 filed on Mar. 11, 2010.

INDUSTRIAL APPLICABILITY

The present invention is applicable to allocation of resources to a plurality of applications operated on a computer.

REFERENCE SIGNS LIST

-   100 RESOURCE ALLOCATION APPARATUS -   110 PARAMETER DETERMINATION UNIT -   120 RESOURCE AMOUNT DETERMINATION UNIT -   200 RESOURCE ALLOCATION APPARATUS -   210 PARAMETER DETERMINATION UNIT -   220 RECEPTION UNIT -   222 INCREASE BUTTON -   224 DECREASE BUTTON -   230 PARAMETER ADJUSTMENT UNIT -   226 ADJUSTMENT BAR -   240 RESOURCE AMOUNT DETERMINATION UNIT -   222 INCREASE BUTTON -   224 DECREASE BUTTON -   226 ADJUSTMENT BAR -   300 RESOURCE ALLOCATION APPARATUS -   310 PARAMETER DETERMINATION UNIT -   320 RESOURCE NUMBER CONTROLLER -   330 RESOURCE AMOUNT DETERMINATION UNIT -   AQ UNIFORM QUALITY OF EXPERIENCE -   A FIRST PARAMETER -   B SECOND PARAMETER -   TR PREDETERMINED AMOUNT 

1-7. (canceled)
 8. A resource allocation apparatus for performing allocation of an amount of resources to a plurality of applications operated on a computer, the resource allocation apparatus comprising: parameter determination means for determining, for each of the plurality of applications, a first parameter a and a second parameter b in a quality function f of expression (1) indicating a relation between an amount of resources to be used and a quality of user experience; and resource amount determination means for determining an amount of resources to be allocated to the plurality of applications using the quality function f for each of the plurality of applications in which the first parameter a and the second parameter b are determined by the parameter determination means, wherein the parameter determination means substitutes, for each of the applications, a recommended amount of resources and a quality of experience corresponding to the recommended amount of resources, and a minimum amount of resources and a quality of experience corresponding to the minimum amount of resources into expression (1), to calculate the first parameter a and the second parameter b in expression (1), and the quality function f(x) is a monotonically increasing function having an inverse function f⁻¹, connects (−∞, 0) and (+∞, 1), and is symmetrical with respect to x=0: Q=f(x)=f((R−a)/b)   (1), where Q: quality of experience; f: quality function; R: amount of resources; a: first parameter; and b: second parameter.
 9. The resource allocation apparatus according to claim 8, further comprising: reception means for receiving an increase/decrease request of an amount of resources for any one of the plurality of applications; and parameter adjustment means for multiplying, for the any one of the applications, the first parameter a and the second parameter b determined by the parameter determination means by a multiple number larger than one, the number increasing according to an increase amount indicated by the increase/decrease request received by the reception means, the parameter adjustment means multiplying the first parameter a and the second parameter b by a multiple number smaller than one, the number decreasing according to a decrease amount indicated by the increase/decrease request received by the reception means, wherein the resource amount determination means determines, for the any one of the applications, the amount of resources to be allocated to the application using the quality function fin which the first parameter a and the second parameter b are adjusted by the parameter adjustment means.
 10. The resource allocation apparatus according to claim 8, wherein the resource amount determination means determines the amount of resources to be allocated to the plurality of applications so that a total amount of resources to be allocated to the plurality of applications is a predetermined amount, and the quality of experience of each of the applications is a uniform quality of experience of the same value.
 11. The resource allocation apparatus according to claim 9, wherein the resource amount determination means determines the amount of resources to be allocated to the plurality of applications so that a total amount of resources to be allocated to the plurality of applications is a predetermined amount, and the quality of experience of each of the applications is a uniform quality of experience of the same value.
 12. The resource allocation apparatus according to claim 10, further comprising resource number control means for performing control, when there are a same type of a plurality of resources, so that the number of resources to be allocated to the plurality of applications becomes a minimum number under a condition that the uniform quality of experience is equal to or larger than a predetermined certain threshold.
 13. The resource allocation apparatus according to claim 11, further comprising resource number control means for performing control, when there are a same type of a plurality of resources, so that the number of resources to be allocated to the plurality of applications becomes a minimum number under a condition that the uniform quality of experience is equal to or larger than a predetermined certain threshold.
 14. The resource allocation apparatus according to claim 8, wherein the quality function f(x) is one of expression (2) and expression (3): f(x)=1/(1+ê(−x))   (2) f(x)=(1/π)×arc tan(x)+1/2   (3).
 15. A resource allocation method for performing allocation of an amount of resources to a plurality of applications operated on a computer, the resource allocation method comprising: for each of the plurality of applications, substituting a recommended amount of resources and a quality of experience corresponding to the recommended amount of resources, and a minimum amount of resources and a quality of experience corresponding to the minimum amount of resources into a quality function f of expression (4) indicating a relation between an amount of resources to be used R and a quality of user experience Q, to determine a first parameter a and a second parameter b; and determining an amount of resources to be allocated to the plurality of applications using the quality function f for each of the plurality of applications in which the first parameter a and the second parameter b are determined, wherein the quality function f(x) is a monotonically increasing function having an inverse function f⁻¹, connects (−∞, 0) and (+∞, 1), and is symmetrical with respect to x=0: Q=f(x)=f((R−a)/b)   (4), where Q: quality of experience; f: quality function; R: amount of resources; a: first parameter; and b: second parameter.
 16. A non-transitory computer readable medium storing a program for causing a computer to execute, when performing allocation of an amount of resources to a plurality of applications operated on a computer, the following processing of: for each of the plurality of applications, substituting a recommended amount of resources and a quality of experience corresponding to the recommended amount of resources, and a minimum amount of resources and a quality of experience corresponding to the minimum amount of resources into a quality function f of expression (5) indicating a relation between an amount of resources to be used R and a quality of user experience Q, to determine a first parameter a and a second parameter b; and determining an amount of resources to be allocated to the plurality of applications using the quality function f for each of the plurality of applications in which the first parameter a and the second parameter b are determined, wherein the quality function f(x) is a monotonically increasing function having an inverse function f⁻¹, connects (−∞, 0) and (+∞, 1), and is symmetrical with respect to x=0: Q=f(x)=f((R−a)/b)   (5), where Q: quality of experience; f: quality function; R: amount of resources; a: first parameter; and b: second parameter. 